6533b7d9fe1ef96bd126ccb9
RESEARCH PRODUCT
FLP estimation of semi-parametric models for space-time point processes and diagnostic tools
Giada AdelfioMarcello Chiodisubject
Statistics and ProbabilityComputer scienceSpace timeR packageProbability and statisticsManagement Monitoring Policy and LawSpace-time point processePoint processSemiparametric modelTerm (time)ETAS modelComputers in Earth ScienceComponent (UML)StatisticsCode (cryptography)Computers in Earth SciencesAlgorithmEtasFLPParametric statisticsdescription
Abstract The conditional intensity function of a space–time branching model is defined by the sum of two main components: the long-run term intensity and short-run term one. Their simultaneous estimation is a complex issue that usually requires the use of hard computational techniques. This paper deals with a new mixed estimation approach for a particular space–time branching model, the Epidemic Type Aftershock Sequence model. This approach uses a simultaneous estimation of the different model components, alternating a parametric step for estimating the induced component by Maximum Likelihood and a non-parametric estimation step, for the background intensity, by FLP (Forward Predictive Likelihood). Moreover, proper graphical tools for diagnostics have been developed and collected, together with the used implemented code in a R package here introduced, named etasFLP .
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-11-01 |